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DataOps For Business Analytics Teams

DataKitchen

Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. Data tables from IT and other data sources require a large amount of repetitive, manual work to be used in analytics. In business analytics, fire-fighting and stress are common.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

How effectively and efficiently an organization can conduct data analytics is determined by its data strategy and data architecture , which allows an organization, its users and its applications to access different types of data regardless of where that data resides.

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Convergent Evolution

Peter James Thomas

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

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A Simple Data Capability Framework

Peter James Thomas

Collation of Data to provide Information. This area includes what is often described as “traditional” reporting [3] , Dashboards and analysis facilities. Data Architecture / Infrastructure. When I first started focussing on the data arena, Data Warehouses were state of the art.

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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

With Stripe Data Pipeline for Amazon Redshift, we’re helping our customers set up a direct and reliable data pipeline in a few clicks.

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The latest edition of The Data & Analytics Dictionary is now out

Peter James Thomas

Business Glossary (contributor: Tenny Thomas Soman ). Data Architecture – Definition (2). Data Catalogue. Data Community. Data Domain (contributor: Taru Väre ). Data Enrichment. Data Federation. Data Function. Data Model. Data Operating Model. Chart (Graph).

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard. Beyond the technical aspects, the goals are far loftier.